COVID-19 stigma and discrimination in a North Indian State: A concurrent mixed method study - Manmeet Kaur; P V. M Lakshmi; Abhishek Sharma; Vijin Pandara Purayil; Nandita Mathur; Vikas Verma (Wolters Kluwer Medknow Publications, 2023)
We measured COVID-19-related stigma and discrimination and its drivers using a concurrent mixed-methods design in Punjab. The simple random sampling was used to select blocks, subcenters, and urban primary healthcenters from each of the four selected districts. The systematic random sampling was used to select households. A sample of 423 adults was interviewed using a structured questionnaire and 10 in-depth interviews were conducted using an interview guide. Binary logistic regression was performed to find the predictors. Stigma prevalence was mild 18%, moderate 45%, and severe 37%. Logistic regression indicated that stigma was lower in the rural compared to the urban population (P < 0.01). Hospitalized patients faced discrimination more often compared to those who were treated/quarantined at home. People feared police (71%), testing (69%), and contracting the infection (65%). Fear of screening, disclosure of status, and transmission of the virus were the drivers of stigma and discrimination. Co-occurrence of labeling, stereotyping, and cognitive separation was observed.